Statistical inference with a manifold-constrained RNA velocity model uncovers cell cycle speed modulations

Computational notebooks and data for exploratory analysis of cell cycle velocity presented in the figures of the manuscript "Statistical inference with a manifold-constrained RNA velocity model uncovers cell cycle speed modulations" by Lederer et al (2024).

Many datasets are adapted from their previously published sources, including:

1. Buettner, F. et al. Computational analysis of cell-to-cell heterogeneity in single-cell RNA-sequencing data reveals hidden subpopulations of cells. Nat. Biotechnol. 33, 155–160 (2015). 

2. Riba, A. et al. Cell cycle gene regulation dynamics revealed by RNA velocity and deep-learning. Nat. Commun. 13, 2865 (2022). 

3. Capolupo, L. et al. Sphingolipids control dermal fibroblast heterogeneity. Science 376, eabh1623 (2022). 

4. Aissa, A. F. et al. Single-cell transcriptional changes associated with drug tolerance and response to combination therapies in cancer. Nat. Commun. 12, 1628 (2021).

5. La Manno, G. et al. Molecular architecture of the developing mouse brain. Nature 596, 92–96 (2021).

6. Replogle, J. M. et al. Mapping information-rich genotype-phenotype landscapes with genome-scale Perturb-seq. Cell 185, 2559-2575.e28 (2022).